Senior Manager, GenAI Engineer Specialist

Deloitte•Atlanta, GA

5d•$159,000 - $292,900

About The Position

Role Overview : As a Senior Manager, GenAI Engineer Specialist , you will be the visionary and driving force behind our GenAI strategy, roadmap, and implementation. Your role will encompass all aspects that are necessary to make GenAI part of everything we do: how we build products (GenAI-powered SDLC activities) and what we build (GenAI infusion into features & functionalities). You will get to be hands-on most of the time and will lead by example, act as role model, actively engaging in high-visibility projects while mentoring and guiding engineers. This role demands a deep understanding of AI/ML/GenAI technologies, leadership acumen, and a passion for driving innovation. The ideal candidate will lead engineers and collaborate with cross-functional teams to design, develop, and deploy advanced AI/ML/GenAI solutions. Recruiting for this role ends on 1/11/2026. The team : US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte's primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte's success. It is the engine that drives Deloitte, serving many of the world's largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

Requirements

A bachelor's degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor.
12+ years of hands-on applied experience in AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like prompt engineering, fine-tuning, etc.
Strong understanding and experience in managing big data of various forms to generate insights and create intelligence.
Proven experience in: Python, R, TensorFlow, PyTorch, Keras, C#, Julia, ML libraries, NLP, NodeJS, Javascript, Streamlit, etc.
Strong experience with cloud hyper-scalers like AWS, Azure, GCP to build cloud-native applications.
Expertise in modern software engineering practices, including Agile methodologies, DevSecOps, SRE, MLOps, deployment techniques like Blue-Green, Canary to enable A/B testing approaches.
Proven track record of leading and managing high-performing engineering teams.
Exceptional interpersonal and organizational skills as well as strategic mindset with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.
Ability to travel 0-20%, on average, based on the work you do and the clients and industries/sectors you serve

Responsibilities

Strategic Vision and Alignment: Craft and articulate a vision for GenAI as it specifically applies to the product engineering teams in alignment with the US Deloitte Technology GenAI strategy. Collaborate with diverse stakeholders, including product, engineering, experience, delivery, security, and infrastructure teams.
Advocacy and Technology Roadmap: Advocate for, develop, and communicate the GenAI implementation approach to the product engineering teams. Ensure the organization is well-informed about objectives, KPIs, technology roadmaps, and progress.
Craft Mastery and Objectives Realization: Define, measure, and drive the achievement of KPIs. Establish and evolve AI/ML/GenAI domain standards and best practices. Actively be hands-on with design, architecture, and code most of the time, contributing to team velocity, and be actively engaged with engineers across SSDLC. Review code, drive tech debt reduction, and experiment with new tech.
Capability Evolution and Development: Mentor and develop engineers. Coach and develop skills in modern engineering practices, related to AI/ML/GenAI. Showcase learning and mastery by showcasing experiments internally, speaking at conferences, writing whitepapers or blogs, and leading R D collaborations.
Iterative Value Delivery: Embrace an iterative/incremental approach to product engineering. Apply a learning-forward approach to navigate complexity and uncertainty. Ensure alignment with customer and business goals through iterative steps and empirical evidence.
Customer-Centric Problem Solving: Focus on addressing critical issues faced by customers and users. Align technical solutions with business objectives. Minimize unnecessary technical complexities and overengineering. Drive teams toward peak performance through continuous learning and improvement.
Expert Proficiency and Continuous Improvement: Possess deep expertise in modern software engineering practices. Identify inefficiencies and opportunities for innovation. Enhance the product engineering operating model to be lean and adaptable. Guide and transform the organization to embrace lean principles and foster a culture of innovation.
Tech/Quality Risk Management: Ensure appropriate technology use and adoption by engineers. Develop and implement explainable, scalable, reliable, and secure products. Inspire experimentation and quality of code. Identify potential technical risks and develop mitigation strategies.
Influential Communication: Influence, persuade, and drive decision-making processes. Communicate effectively in both written and verbal forms. Craft clear, structured arguments and technical trade-offs supported by evidence.
Organizational Engagement and Collaboration: Engage stakeholders at all levels of the organization. Build collaborative and constructive relationships. Co-create and drive momentum and value across multiple organizational levels.